AI Application Engineer

🕒 January 20

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Rearc

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

Artificial Intelligence • Cloud

Rearc is a boutique, engineering-driven services firm specializing in cloud, data, and generative AI solutions. They are known for their innovation and engineering delivery excellence, empowering small teams to achieve significant results and foster creativity. Rearc offers services such as GenAI quickstart, secure data collaboration, data platform foundation, and cloud platform engineering. Their services are comprehensive and adaptable to meet the specific needs of their clients. Rearc has expertise in building foundational data platform capabilities, cloud governance, and the use of AWS products.

📋 Description

• Collaborate with Colleagues – Work closely with colleagues to understand customers' business objectives and technical challenges, contributing to the design and development of effective GenAI solutions tailored to client needs. • Apply GenAI Principles – Utilize modern tools and frameworks like LangGraph, to build scalable, reliable, and maintainable Compound AI systems. • Leverage your understanding of AI fundamentals to ensure every project meets rigorous industry and ethical standards. • Adapt to the latest Technologies & Patterns – continue to research, learn, and stay abreast of the most recent state of the art for AI application development. • Promote Knowledge Sharing –Bolster our culture of continuous learning by sharing knowledge about AI engineering best practices through blog posts, articles, and internal talks.

🎯 Requirements

• 2+ years of experience in AI engineering, machine learning (ML), or related fields • Strong understanding of state of the art techniques in generative AI, including large language models (LLMs), text generation and other foundation models • Familiarity with AI orchestration tools (e.g. LangGraph, CrewAI, Bedrock Agents, smolagents, etc) • Experience in fine-tuning, prompt engineering or otherwise adapting generative models for specific use cases • Experience with AI model evaluation, including human-in-the-loop and LLM judge paradigms • Familiarity with NLP libraries and frameworks • Hands-on experience in implementing Retrieval Augmented Generation (RAG) architectures and integrating retrieval systems with generative models • Knowledge of at least one vector store or database (e.g. Opensearch, Pinecone, PostgreSQL with pgvector) and techniques for similarity search • Familiarity with common data ingestion/ETL patterns for populating knowledge bases • Experience with implementing LLM tool calling (either directly, via an orchestration framework, or using Model Context Protocol (MCP) clients) • Experience using Amazon Bedrock or Databricks Mosaic AI for deploying and managing generative AI models • Strong programming skills in Python (or similar languages) • Familiarity with CI/CD pipelines and MLOps practices to ensure seamless integration, testing and deployment of AI models

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events